10-601 SVMs and Margin Classifiers 2
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Revision as of 09:53, 12 August 2014 by Zivbj (talk | contribs) (Created page with "This a lecture used in the Syllabus for Machine Learning 10-601 in Fall 2014 === Slides === * TBD === Readings === * === What You Should Know Afterward === * Dual f...")
This a lecture used in the Syllabus for Machine Learning 10-601 in Fall 2014
Slides
- TBD
Readings
What You Should Know Afterward
- Dual formulation of SVMs
- Meaning of variables in the dual solution
- Non linearly separable dual
- Dependence of variables on the number of features
- Feature transformation and the kernel trick
